Ground Penetrating Radar Scanning Research Articles

Comparative Study on NDT Techniques for Evaluation of Concrete Quality Exposed to Marine Environment

Concrete, the primary material used in quay walls, is directly exposed to saline environments. Coping concrete, particularly in areas where periodic berthing and loading/unloading occur, is prone to rapid quality deterioration. Current facility safety and maintenance guidelines assess concrete durability at specific points through sampling, which are intended to represent the entire inspection unit. This paper explores quality management strategies from an areal perspective by applying various non-destructive scanning methods to extensive areas of coping concrete. Ultrasonic array imaging and ground-penetrating radar scanning images revealed significant quality degradation in berthing operation areas, whereas sampling-based ultrasonic pulse velocity and rebound hardness values were less effective in detecting this degradation.

Ground-penetrating radar scanning and historical interpretation of the location of the destroyed Epiphany Cathedral in Kyiv Brotherhood Monastery (Ukraine)

Background The article presents results of a ground penetrating radar (GPR) scanning carried out in a site of the Epiphany Cathedral of Brotherhood Monastery in Kyiv, Ukraine, destroyed in 1936 by the Soviets. The Cathedral is known as a burial site of Hetman Petro Sahaidachnyi (1582–1622), a Ukrainian Cossack political and civic leader, guardian and patron of Kyiv Brotherhood Monastery. The collection of archival documents, blueprints, stock sources, photographs and cartographic materials of the 17th-19th centuries, as well as historical works of the 19th-21st centuries, were thoroughly analyzed and used as a basis for the interpretation of geophysical results. The set of historical data covers the period from 1615, that is, from the beginning of the construction of the wooden Epiphany Church, the predecessor of the cathedral, to the present day. Methods Summarized information about the construction, restoration after the fire, functioning and destruction of the Cathedral, as well as about the construction on its site in the 20th century, archaeological research in the 20th-21st centuries, was used to clarify possible location of hidden foundations and target GPR measurements. In this context, written testimonies of archaeologists who personally observed the foundations of the cathedral became especially valuable. The shielded GPR antennas, with a central frequency of 300 MHz and 700 MHz, is used for non-invasive investigation. Results GPR scanning specified the site and showed the best-preserved group of foundations of the western wall of the Epiphany Cathedral. Conclusions An integrated historical and geophysical study provided the basis to certify the foundation of the Epiphany Cathedral as a protected object of cultural heritage and facilitated its archaeological research.

DETECTION OF DISTRICT HEATING PIPELINE USING UAVMOUNTED THERMAL CAMERA AND GPR SCANNING

<p>In this paper the benefits of integration of UAV-mounted (Unmanned Aerial Vehicle) thermal camera and GPR (Ground Penetrating Radar) are analysed. As an example we analized a district heating pipeline in a part of university campus in Novi Sad. Thermal camera mounted on UAV enables fast mapping of routes. These data are then used to detect critical zones where leaking or some other problem occurs and to validate utility cadastral data. Detailed inspection of zones is done using GPR scanning. This provides data such as geometry, precise location of damage, etc. In the last section of the paper advantages of non-invasive detection of district heat line combining active and passive sensors with UAV are explained.</p>

A reinforcement learning (RL)-based hybrid method for ground penetrating radar (GPR)-driven buried object detection

Ground penetrating radar (GPR) systems are effective sensors for discovering various types of objects buried underground, such as military mines, metal objects, and pieces of underground infrastructures. A GPR system can be manually operated by a human or can be an integral part of a host platform. The host platform may be semi- or fully autonomous and may operate in different environments such as land vehicles or more recently air-borne drones. One challenge for the fully or semi-autonomous host platforms in particular is to find an efficient search procedure that would reduce the operation time and optimize resource utilization. Most of the current approaches are based on pre-defined search patterns which, for large and sparse areas, could mean unnecessary waste of time and resources. In this paper, we introduce a method that combines a coarse and therefore relatively low cost initial search pattern with a Reinforcement Learning (RL) driven efficient navigation path for eventual target detection, by exploiting the signal processing pipeline of the onboard GPR. We illustrate the applicability of the method using a well-known, high fidelity GPR simulation environment and a novel RL framework. Our results suggest that combination of a coarse navigation scheme and an RL-based training procedure based on GPR scan returns can lead to a more efficient target discovery procedure for host platforms.

Unveiling a hidden fortification system at “Faraglioni” Middle Bronze Age Village of Ustica Island (Palermo, Italy) through ERT and GPR prospections

We carried out a geophysical research project in the Middle Bronze Age village of Ustica (Palermo, Sicily, Italy), named “Faraglioni Village” after the stack formations which detach from the coast north of the archaeological site. The investigation, which comprised Electrical Resistivity Tomography (ERT) and Ground Penetrating Radar (GPR) techniques, allowed us to discover the buried foundations of an outwork fortification system never evidenced by previous archaeological studies, only hypothesised from the observation of aerial photography and partially outcropping boulders, which align roughly parallel to the main defensive wall of the Village.Our geophysical prospection involved the entire 250 m-long arc of the outward village defensive wall, with the acquisition of eleven ERT profiles and 27 GPR scans. The techniques were selected based on both favourable logistics and methods applicability: ERT sections allowed us to trace a series of high-resistivity anomalies arranged to form an arc-shaped structure along the perimeter of the defensive wall. GPR investigation was localised in the most accommodating patch of terrain of the site, with the effort of intercepting clear enough sections of the target, to determine more accurately its shape, depth, and overall dimensions. Our discovery paves the way for new investigations, mainly aimed at defining the timing of construction of the fortification system, as well as the function of the remains of other architectural structures identified close to the wall, which could represent the target of further geophysical investigations.

Ground Penetrating Radar Scanning and Historical Interpretation of the Location of Kyiv Confraternal Monastery’s Epiphany Cathedral

In 2021, we performed a ground penetrating radar survey at the place of the Epiphany Cathedral of the Kyiv Confraternal Monastery, destroyed in 1936, in order to precisely locate its foundations. The collection and analysis of archival information from open sources was carried out, which became the basis for the interpretation of the results of geophysical measurements. Publications and written testimonies of archaeologists who personally saw the foundations of the Cathedral became especially valuable. The set of historical data covers the period from 1615, that is, from the beginning of the construction of the wooden Epiphany Church, the predecessor of the Cathedral, to the present day. Original documents, blueprints, stock sources, photographs, and cartographic materials of the 17th––19th centuries, as well as historical works of the 19th–21st centuries, were analyzed. The information about the construction, restoration after the fire, functioning, and destruction of the Cathedral, as well as about the construction on its site in the 20th century, archaeological research in the 20th–21st centuries was generalized. Ground penetrating radar survey revealed the best-preserved group of foundations of the western wall of the Cathedral, which are proposed for archaeological excavations.

Ground-penetrating radar scanning and historical interpretation of the location of the destroyed Epiphany Cathedral in Kyiv Brotherhood Monastery (Ukraine).

The article presents results of a ground penetrating radar (GPR) scanning carried out in a site of the Epiphany Cathedral of Brotherhood Monastery in Kyiv, Ukraine, destroyed in 1936 by the Soviets. The Cathedral is known as a burial site of Hetman Petro Sahaidachnyi (1582-1622), a Ukrainian Cossack political and civic leader, guardian and patron of Kyiv Brotherhood Monastery. The collection of archival documents, blueprints, stock sources, photographs and cartographic materials of the 17th-19th centuries, as well as historical works of the 19th-21st centuries, were thoroughly analyzed and used as a basis for the interpretation of geophysical results. The set of historical data covers the period from 1615, that is, from the beginning of the construction of the wooden Epiphany Church, the predecessor of the cathedral, to the present day. Summarized information about the construction, restoration after the fire, functioning and destruction of the Cathedral, as well as about the construction on its site in the 20th century, archaeological research in the 20th-21st centuries, was used to clarify possible location of hidden foundations and target GPR measurements. In this context, written testimonies of archaeologists who personally observed the foundations of the cathedral became especially valuable. The shielded GPR antennas, with a central frequency of 300 MHz and 700 MHz, is used for non-invasive investigation. GPR scanning specified the site and showed the best-preserved group of foundations of the western wall of the Epiphany Cathedral. An integrated historical and geophysical study provided the basis to certify the foundation of the Epiphany Cathedral as a protected object of cultural heritage and facilitated its archaeological research.

Clutter Effect on a Combination of Microwave Imaging and Target Identification Using Ground-Penetrating Radar

This paper presents an experimental investigation of the effect of clutter on the performance of microwave imaging and target identification using ground-penetrating radar (GPR) for buried objects. Signals collected by the GPR were formed to be B-scan and 3D images to carry out the microwave imaging of buried objects. Poles extracted using the short-time matrix pencil method from a late-time response of the received signal collected at a specific position were exploited to identify buried objects. The experiment was set up by constructing a large box filled with sand where an L-shaped metallic sheet was buried. The GPR was installed along with a 2-dimensional scanner above the box to image and identify the buried metallic sheet. In order to investigate the effect of the clutter on the performance of the GPR-based microwave imaging and target identification, small rocks were arranged on the sand surface, and their density was then varied. The experimental results have shown that clutter density significantly affects the sharpness of the B-scan and 3D images. The rocks result in an additional surface layer in the images. Moreover, the results have also shown that the clutter does not affect the performance of the identification of the buried object. From the results, the poles obtained from the GPR scanning inside and outside the buried object region differed. This confirms that the poles of the buried object should be different from those without the object. The poles of the buried object remain constant, although rocks on the sand surface exist since the clutter affects only the early-time response (not the late-time response). With varying clutter densities, the underlying poles were significantly changed, but this does not affect the identification of the buried object.

Damage tracking in laboratory reinforced concrete bridge columns under reverse-cyclic loading using fusion-based imaging

ABSTRACT Fusion-based imaging using ground-penetrating radar (GPR) and ultrasonic echo array (UEA) was employed to track damage progression in the columns of two full-scale reinforced concrete (RC) bridge column-footing subassembly laboratory specimens. The specimens had different lap-splice detailing and were subjected to reverse-cyclic lateral loading simulating a subduction zone earthquake. GPR and UEA scans were performed on the east and west faces of the columns at select ductility levels. Reconstructed images were obtained using the extended total focusing method (XTFM) and fused using a wavelet-based technique. Composite images of each column's interior were created by merging the images from both sides. A quantitative analysis based on the structural similarity (SSIM) index accurately captured damage progression. A backwall analysis using the amplitude of the backwall reflector was also performed. Changes as early as in the first measurement (μ = 0.5 displacement ductility level) could be detected. Damage variation along the column height was observed, consistent with greater damage at the base. The proposed analyses distinguished the structural behavior differences between the two specimens. In summary, the SSIM metric provides a valuable tool for detecting changes, while the backwall analysis offers simple yet informative insights into damage progression and distribution in full-scale RC members.

Numerical Study on Urban Infrastructure Diagnosis in Laterally Heterogenous Soils Using Resistivity and Ground Penetrating Radar Techniques

Urban environment can be considered a complex system consisting of the engineered pavement physical structure over the buried utilities (water, gas, sewer) network embedded in the background soil environment. Assessment of buried pipeline civil infrastructures using proximal geophysical methods in such instances has to consider possible interferences, difficulties, and incorrect inferences. In this study, we have conducted a numerical modelling investigation to understand and evaluate how electrical resistivity profiling (ERP) and ground penetrating radar (GPR) can be utilised to provide subsurface information that otherwise may not be possible if either one of the techniques is used. A model geometry consisting of a typical pavement structure (asphalt, base/subbase, and background soil) with a single 2 m pipe buried at a depth of 1 m was used. Strong lateral variations in soil type were incorporated over the short pipe section in order to understand the complexities that can arise, especially with ERP measurements. The 3D electrical resistivity measurements were simulated in Comsol using the 4-probe method, while the 2D GPR measurements were simulated in gprMax to obtain the subsurface information. The results from both ERP and GPR were used to develop a practical framework that can be utilised by relevant authorities for proximal condition assessment of their buried assets. It was suggested that ERP can be used as a first level screening tool over the whole pipeline length, followed by discretely selected GPR scans in order to further gain information on the pipe health. This is attractive practically since, following delineations of a large pipe section into shorter subsections, advanced condition assessment approaches that are generally intrusive in nature can then be economically deployed within the subsections suspected of experiencing significant corrosion damage.

Evaluation of the effects of elevated CO2 concentrations on the growth of cassava storage roots by destructive harvests and ground penetrating radar scanning approaches.

Cassava (Manihot esculenta Crantz) production will need to be improved to meet future food demands in Sub-Saharan Africa. The selection of high-yielding cassava cultivars requires a better understanding of storage root development. Additionally, since future production will happen under increasing atmospheric CO2 concentrations ([CO2 ]), cultivar selection should include responsiveness to elevated [CO2 ]. Five farmer-preferred African cassava cultivars were grown for three and a half months in a Free Air CO2 Enrichment experiment in central Illinois. Compared to ambient [CO2 ] (~400 ppm), cassava storage roots grown under elevated [CO2 ] (~600 ppm) had a higher biomass with some cultivars having lower storage root water content. The elevated [CO2 ] stimulation in storage root biomass ranged from 33% to 86% across the five cultivars tested documenting the importance of this trait in developing new cultivars. In addition to the destructive harvests to obtain storage root parameters, we explored ground penetrating radar as a nondestructive method to determine storage root growth across the growing season.

Different techniques in detection of buried objects using ground-penetrating radar: A review

This literature reviews the work of researchers on ground-penetrating radar (GPR). This research consists of five sections starting from the first section that focuses on the general application and the advantage of the GPR system in comparison to other types of underground detection systems.
 The main function of the GPR system is to detect the object buried underground and at the end of the full scan, the output image represents the total signals detected by the receiver of the GPR device. One of the main applications of the GPR system is the detection of an underground object, the GPR scans the underground area and the output image represents the total of the signals detected by the receiver. The second section discusses methods for removing unwanted signals such as noise and direct waves from the output image of a GPR system.
 After removing the noise, the image requires further analysis to discover and interpret the buried object. The third section discusses the common methods used in the process of identifying buried objects. There are different types of buried objects and section four discusses the algorithms used to detect and identify landmines and explosive devices.
 Finally, the last section summarizes the paper that discussed the detection and identification process using smart algorithm technology. These types of algorithms are the most accurate, have a lower error rate and are cost-effective.

GPR mapping with mobile mapping sensing and tracking technologies

Ground Penetrating Radar (GPR) is commonly used for detecting and locating underground utilities, as well as identifying water leakages and other buried objects without the need for excavation. To precisely depict the subsurface by GPR, an accurate geo-referencing technique on each GPR scan is also essential. Traditional geo-referencing of GPR scans requires a survey wheel to walk along a predetermined grid, or relies on the Global Navigational Satellite Systems (GNSS) to work under open sky environments where enough satellites are available (Böniger and Tronicke, 2010; Chang, 2016). In this study, we attempt to use a mobile mapping system (MMS) backpack guided by SLAM as the geo-referencing device for synchronizing GPR scans in areas with bad or no GNSS, and is free of control points. The study develops a method to synchronise the SLAM positioning and GPR measurements and then validate the proposed method's precision and accuracy with a site case. It was proved that the integrationed time and labour required in the traditional gridding are minimized for improving the GPR survey efficiency, facilitating the large-scale survey in dense urban areas where good GNSS coverage is unavailable.

Non-Destructive Detection of Asphalt Concrete Stripping Damage using Ground Penetrating Radar

Ground penetrating radar (GPR) is a non-destructive evaluation technique, which has been applied to assess as-built pavement conditions and to evaluate damage and deterioration that develop over time. The objective of this study was to develop a methodology that uses GPR to detect moisture-related stripping damage in asphalt pavements. To achieve this objective, A Finite-Difference Time-Domain based simulation program was used to study the propagation of GPR signals in a stripped pavement. Field test data including GPR scans and visual inspection of cores of 202 pavement sections were used to study the relationship between GPR traces and asphalt concrete (AC) stripping damage. Based on this analysis, a novel GPR-based indicator, known as the accumulating in-layer peaks (AIP), was introduced to detect stripping damage in asphalt pavements. Field data and pavement cores were used to validate the proposed indicator and to evaluate its effectiveness in detecting the presence, extent, and severity of stripping in in-service pavement sections. Based on the results of the study, it was found that the presence of a void in the middle of the AC layer resulted in positive peaks in the reflected waves as indicated by the simulation of GPR signals. In addition, detected intermediate wave peaks between the surface and the interface between the AC and base layers on the GPR traces were associated with stripping damage in the AC layer. The AIP predicted accuracies for stripped and non-stripped sections were 80% and 96%, respectively, indicating its effectiveness in detecting stripping damage in flexible pavements.

Evaluation of GPR Detection for buried objects material with different depths and scanning angles

A Ground-penetrating radar (GPR) is considered an efficient non-destructive device for detecting the buried object. The GPR operation is based on the analysis of the received scattered of the transmitted signal. Its output is the two-dimensional image radiogram hyperbolic curve, this image represents the reflected signal of the buried object. To date, studies investigating targets (buried objects) have produced equivocal results. Therefore, this paper highlights the importance of the effect of changing target-detection parameters (material type, target to surface distance, size, and scan to target location angle) concerning the hyperbolic curve on the GPR experiment image. A practical model has been built for this experiment with three material types (metal, plastic, and pottery) that are buried in the sand soil. Three tests have been done for different types of material, in the different depth for each buried object of the same material. Then, changing the size of the buried object (small and big size), also, changing the location angle of the buried objects concerning the direction of the GPR scan. For these tests, the effect on the hyperbolic curve has been recognized. A MALA 1 GHz geophysical GPR system is used in these experiments. As a result, the strength of the reflected EMW changes concerning the type of material, size, depth, and location angle of the buried object.

Mechanical and durability properties of metakaolin blended with slag geopolymer mortars used for pavement repair

Metakaolin (MK)-based geopolymers are usually treated with heat curing for variable lengths of time, which limit their application to areas beyond prefabricated components. In this paper, an experimental investigation was carried out to study the compressive, flexural, and bond strengths, as well as the dry shrinkage, durability, and microstructural characteristics of MK-based geopolymer mortar cured at ambient conditions for pavement repair with the inclusion of ground granulated blast furnace slag (GGBS) at replacement ratios of 0%–40%. Changes in the mass and strength of the geopolymer and ordinary Portland cement (OPC) mortars subjected to 3.5% sodium chloride solution, 5% sodium sulfate solution, and sulfuric acid solution (pH = 1) were used to investigate durability. In addition, a field application case of alkali-activated MK–GGBS mortar repair material indicated desirable construction based on visual observations and ground-penetrating radar scanning. The microstructures were studied by field emission scanning electron microscopy with energy-dispersive X-ray spectroscopy, X-ray diffraction, and Fourier-transform infrared spectroscopy. The results demonstrated that when the GGBS replacement ratio reached 30%, the mortar performed better than many pavement repair materials, with a desirable compressive strength (75.9 MPa), flexural strength (12.2 MPa), and bond strength (6.42 MPa). It also had a much lower dry shrinkage of 1/4–1 than that of OPC at 28 days with 10% GGBS inclusion. Further, it had superior durability under chemical environments, which can be attributed to fine void-filling particles and the formation of N-A-S-H-type and C-S-H-type gels. The degradation mechanism of the alkali-activated MK–GGBS binary system in a sulfuric acid environment was found to be based mainly on the leaching of metal cations, the destruction of alumina–silicate bonds, and the micro-expansion microcracks of the gypsum phase. A field application of the repair material indicated that it is desirable for construction, allowing for a quick reopening within 6 h, while the repaired pavement still performed well after 4 months of service.

Deep Learning-Based Subsurface Target Detection From GPR Scans

Ground penetrating radar (GPR) has been widely used as a non-destructive technique to detect subsurface objects. Manual interpretation of GPR data is tedious and time-consuming. To address this challenge, an automatic method based on a deep instance segmentation framework is developed to detect and segment object signatures from GPR scans. The proposed method develops the Mask Scoring R-CNN (MS R-CNN) architecture by introducing a novel anchoring scheme. By analyzing the characteristics of the hyperbolic signatures of subsurface objects in GPR scans, a set of anchor shape ratios are optimized and selected to substitute the predefined and fixed aspect ratios in the MS R-CNN framework to improve the signature detection performance. In addition, transfer learning technique is adopted to obtain a pre-trained model to address the challenge of insufficient GPR dataset for model training. The detected and segmented signatures can then be further processed for target localization and characterization. GPR data of tree roots were collected in the field to validate the proposed methods. Despite the noisy background and varying signatures in the GPR scans, the proposed method demonstrated promising results in object detection and segmentation. Computational results show that the improved MS R-CNN outperforms the other state-of-the-art methods.

Fibre-reinforced polymer laminate–concrete bond check with ground penetrating radar

Externally applied carbon-fibre-reinforced polymer (CFRP) laminate is a viable, economic and durable option for strengthening deteriorated, damaged or under-designed concrete structures. Effective stress transfer at the CFRP–concrete interface is an important consideration and quantitative on-site inspection of CFRP application quality is still a challenging issue. In this study, a ground penetrating radar scanning approach was used to examine the bond quality in small-scale concrete beams with flexurally applied CFRP laminates. The parameters considered included the concrete surface roughness, concrete surface voids, epoxy thickness and CFRP type. A three-point bending test and numerical modelling were used to develop simple quantitative relationships between the scanning results and the parametric combinations. Non-destructive evaluation techniques are convenient and provide valuable information for the prediction of the interfacial bond quality and the actual capacity contribution of the CFRP laminate, which will allow a higher confidence level in CFRP application quality and better quality control of concrete structures.

Experimental detection of the volume of the drip irrigation soil wetted body using Ground Penetrating Radar

The accurate detection of the volume of the soil wetted body (SWB) is the theoretical basis for the optimal design of a drip irrigation system. In view of the shortcomings of traditional detection methods, such as low efficiency, high cost, and poor in situ detection, this paper explores the rapid, in situ, and nondestructive estimation techniques of SWB volume using Ground Penetrating Radar (GPR). Through drip irrigation of different water volumes and geotechnical experiments, the SWBs with different sizes were formed in air-dried soil and natural soil, respectively. The GPR scan lines on the ground were arranged to obtain the SWB radargram, and the profile shape of the wetted body was restored by the F-K transformation process (frequency-wave domain migration algorithm) that can transform the wave equation in the time-space domain into the frequency-wavenumber domain to achieve offset homing. On this basis, the SWB volume estimation model was constructed by three methods: regression analysis, geometric calculation, and profile triple integration (profile area accumulation). Additionally, the accuracies of the models were verified by the measured data of the SWB excavation. For each of these methodologies, we illustrate the quality of the output with the measured data and discuss the possibilities and limitations. The results show that the profile triple integration model is not accurate. The regression analysis model has the greatest accuracy. However, owing to the difference in soil characteristics, the model input parameters must be changed. Relatively, the geometric calculation model is the best model to detect the SWB volume. From the results, we can draw a conclusion that the method combining F-K transformation process and the geometric calculation model can accurately measure the volume of SWB, and it has better adaptability in different soils. We demonstrate the GPR as a rapid geophysical tool that can be used successfully to explore the volume of the SWB formed under drip irrigation. This study expands the agricultural application of GPR and provides a new method for in situ nondestructive rapid detections of the SWB volume.

Predicting material properties of concrete from ground-penetrating radar attributes

We present here a laboratory-based experimental protocol that seeks to establish and characterize the relationship between ground-penetrating radar attributes and the mechanical properties (density, porosity, and compressive strength) of typical industry concrete mixes. The experimental data consist of ground-penetrating radar attributes from 900 MHz radargrams that correspond to simultaneously measured physical properties of Portland cement concrete, alkali-activated concrete, and cement mortar. Appropriate regression models are trained and tested on this data set to predict each physical property from ground-penetrating radar attributes. From a small selection of individual attributes, including total phase and intensity, trained random forest regression models predict porosity (R2 = 0.83 from the instantaneous amplitude), density (R2 = 0.67 from the intensity attribute), and compressive strength (R2 = 0.51 from instantaneous amplitude). These novel relationships between physical properties and ground-penetrating radar attributes indicate that material properties could be predicted from the attributes of ordinary ground-penetrating radar scans of concrete.